LAUSR

Abstract The agricultural production faces the inevitable challenges under the climate change conditions which threaten the food security. Under these circumstances, the increase of productivity can be regarded to ensure the food security. The interaction of genetic management determines the performance of given crop and environmental factors, and these elements should be simultaneously considered to have a sustainable production. To enhance the productivity and eco-efficiency of chickpea agro-ecosystems in the west and northwest of Iran, we optimized the genotype (G) × environment (E) × management (M) interactions to access optimum grain yield and water use efficiency using SSM-legume model. Three genotypes, eight locations, and 3 irrigation regimes were considered G, E, and M factors, respectively. The projections of future climate were conducted due to a 5–multi‐model ensemble under two emission scenarios (RCP4.5 and RCP8.5) for 2040–2070 using a methodology introduced by Agricultural Model Intercomparison and Improvement Project (AgMIP). The results indicated that across two RCPs, the climate change increased chickpea grain yield (11%) due to the positive effects of rising CO2 concentration which slightly increased WUE (0.03%) based on an increase in the evapotranspiration (10.9%) and mean temperature (3.4%) and a decrease during the chickpea growing period (21.9%). However, these decreases and increases can be mitigated and boosted using an optimal G × E × M combination. ILC482 (mid-maturity genotype) × cold northwest environment × SI Pod-60 (supplementary irrigation of 60 mm at pod filling) was the best G × E × M interaction due to optimum WUE (6.98 kg ha-1 mm-1) and grain yield (1808.4 kg ha-1) for chickpea agro-ecosystems in upcoming period (2040–2070). In general, climate change and rising CO2 concentration open up the opportunities to produce more grain yield in chickpea agro-ecosystems. Moreover, this production can be sustainably generated regarding WUE by adopting a suitable G × E × M interaction.